Near real-time surveillance of the SARS-CoV-2 epidemic with incomplete data.

ABSTRACT: When responding to infectious disease outbreaks, rapid and accurate estimation of the epidemic trajectory is critical. However, two common data collection problems affect the reliability of the epidemiological data in real time: missing information on the time of first symptoms, and retrospective revision of historical information, including right censoring. Here, we propose an approach to construct epidemic curves in near real time that addresses these two challenges by 1) imputation of dates of symptom onset for reported cases using a dynamically-estimated "backward" reporting delay conditional distribution, and 2) adjustment for right censoring using the NobBS software package to nowcast cases by date of symptom onset. This process allows us to obtain an approximation of the time-varyin

SUBMITTER: De Salazar PM 

PROVIDER: S-EPMC9004750 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature